1. Field of Invention
Aspects of the present invention relate to video tracking of various objects. More particularly, various aspects of the present invention relate to video tracking of objects using dynamic separation of foreground and background.
2. Description of Related Art
While remote monitoring systems relying on an imaging device, such as a television (TV) camera have been conventionally used in a wide range of applications, many of these applications require manned monitoring systems, which employ a watchperson who supervises a monitor while viewing images displayed on the monitor. In this type of manned monitoring system, a watchperson is required to watch images displayed on a monitor at all times to identify in real time an intruding object, such as a person, a car, or the like, which can come into a field of view being monitored. In effect, a heavy burden is placed on the watchperson, since the watchperson must use their visual ability to detect moving objects and/or persons in the field of view. Because a watchperson has inherently human limitations in concentration and visual ability, the manned monitoring system can experience overlooked intruding objects, which should not be ignored, and therefore has a reliability problem. Also, as monitoring cameras become increasingly widespread, a single watchperson often monitors images from a number of cameras such as, for example, TV cameras on a plurality of monitors at the same time. The watchperson can also overlook an intruding object when a plurality of cameras must be simultaneously monitored.
Therefore, an automatic tracking monitoring system would be useful for automatically detecting an intruding object through image processing of images captured by cameras, instead of the traditional human-based monitoring. Among other things, such an automated system may be needed that will automatically adjust the visual field, viewing direction, and viewing angle of the cameras, in accordance with motions of the intruding object, and, for example, generate a predetermined report and/or alarm.
Target tracking is a core function widely used in many automated video systems. The basic idea of target tracking is to match object appearance across different and successive images. Video trackers often have the dilemma of the background interfering with the foreground during the tracking of a moving person or object. Background pixels within a target tracking box, which is a theoretical box surrounding the moving object or person, go through the same mathematical transformation as the foreground pixels, and thus hinder true target matching. In the related art, background pixels within a target tracking box have been a nuisance. For example, one aspect of background pixels is that they change from frame to frame with respect to the target tracking box, while foreground pixels within the target tracking box are more consistent, since they correspond to the object or person being tracked.
Most related art solutions aim to reduce the influence of background pixels through exploiting temporal consistency in the appearance, structure, motion, and the statistical signature of the foreground pixels. However, one fundamental issue of background disruption is that the foreground has not been directly and effectively addressed, thereby creating video trackers vulnerable to imperfect initial target segmentation and appearance morphing. A reliable dynamic foreground and background separation mechanism would dramatically boost video tracker performance.